JPH0252971B2 - - Google Patents

Description

[Detailed description of the invention]

The present invention relates to a failure diagnosis device for a rotating machine that has a function of automatically determining the cause of a failure of the rotating machine using vibration signals generated from the rotating machine. In general, in order to analyze vibration signals obtained from rotating machines, frequency analysis is performed on digital signals that are A/D converted at intervals synchronized with changing rotation, and characteristic characteristics representing the operating state of the rotating machine are analyzed. As a result of frequency component order ratio analysis, it is necessary that the signal/noise (S/N) ratio is excellent. Furthermore, it is desirable to be able to automatically estimate the cause of a failure based on the feature values obtained from the order ratio analysis, without being affected by the type, size, rotation speed, or load condition of the rotating machine being diagnosed. Conventionally, diagnosis of rotating machinery has been performed using general-purpose signal analysis equipment, and it has been difficult to collect data in a form that allows order ratio analysis. Furthermore, in order to evaluate the state of machine deterioration based on the results obtained from normal frequency analysis and probability density analysis of vibration amplitude, a great deal of knowledge regarding equipment diagnosis accumulated over many years of experience is required. The drawback was that judgments varied due to differences in model, size, or individual differences. SUMMARY OF THE INVENTION An object of the present invention is to provide a diagnostic device for a rotating machine that has a signal input section that can collect vibration signals of the rotating machine in a form that allows order ratio analysis, and that can automatically determine the cause of failure based on various analysis results. The present invention will be explained below based on the drawings. FIG. 1 is a block diagram showing one embodiment of the present invention. In FIG. 1, 1 is a vibration signal input terminal;
2 is a rotation pulse signal input terminal, 3 is a signal input section,
4 is a failure cause estimation unit, 5 is a failure cause table storage unit, 6
indicate the result display section, respectively. In this failure diagnosis device, an analog signal of vibration from a rotating machine (not shown) to be diagnosed, such as a motor, a blower, a gear, etc. is sent from a vibration signal input terminal 1, and a rotation pulse signal is sent from a rotation pulse input terminal 2 to a signal input section 3. take in. FIG. 2 shows an example of a vibration analog signal 7 taken in from the vibration signal input terminal 1 and an example of a rotation pulse signal 8 taken in from the rotation pulse input terminal 2. The signal input unit 3 synchronizes with the rotational pulse signal 8 as described later, multiplies the rotational pulse signal by the rotational frequency to obtain a sampling pulse, uses the sampling pulse as a timing signal to A/D convert the vibration signal 7, and detects a failure. The vibration data S1 is output to the cause estimation unit 4. The failure cause estimation unit 4 performs signal processing such as frequency analysis, order ratio analysis, and amplitude probability density analysis on the input and stored vibration data S1, and calculates a plurality of vibration feature quantities. FIG. 3 shows a display example of the order ratio analysis result as an example of signal processing. Next, calculate the probability of each of the multiple possible failure causes. A database stored in the failure cause table storage unit 5 is used for this calculation, and the results regarding the calculated failure causes are displayed on a result display unit 6 comprised of a CRT, printer, or the like. Next, details of each component and its operation will be explained. FIG. 4 is a block diagram showing details of the signal input section 3. The rotational pulse signal 8 inputted from the rotational pulse signal input terminal 2 is turned into a sampling pulse signal whose rotational frequency is multiplied by the synchronous multiplier circuit 12. The multiplication ratio at this time is determined by selecting the highest analysis order when performing order ratio analysis. The order is called 1st order when the frequency corresponds to the frequency of one rotation, and in order to analyze up to the nth order frequency component, the vibration signal must be sampled at 2n times the rotation frequency. Since the frequency of the rotating pulse signal 8 may vary over time, the synchronous multiplier circuit 12 generates sampling pulses having a set multiplication ratio while being synchronized with the rotating pulse signal 8. Information on this sampling pulse frequency is input to a cutoff frequency control circuit 13 to control the cutoff frequency of the low pass filter 14. The low-pass filter 14 is composed of, for example, a switch capacitor filter whose cut-off frequency is controlled by the sampling pulse frequency or an active filter whose cut-off frequency is controlled by a voltage, and is capable of continuously changing the cut-off frequency. The vibration signal input from the vibration signal input terminal 1 passes through a low-pass filter 14 in order to reduce the aliasing effect that occurs during sampling pulses, and is converted into an A/D converter 15 by an A/D converter 15.
It is converted and output to the failure cause estimation section 4. A/
As the sampling timing pulse of the D converter 15, a sampling pulse generated by the synchronous multiplier circuit 12 is used. Next, a method for estimating the cause of failure will be explained. The failure cause estimation unit 4 performs signal processing such as order ratio analysis, amplitude probability density analysis, and phase analysis on the vibration data S1 input from the signal input unit 3. From these analysis results, for example, the ratio between the primary spectrum value and the vibration effective value, or the ratio between the values of harmonic spectra 9 and 10 and the primary spectrum 11 shown in FIG. 3 ((V ₉ + V ₁₀ )/V ₁₁ ) , or calculate a plurality of feature quantities such as the ratio between the maximum amplitude value and the average value. The failure cause-and-effect table storage unit 5 stores a database showing the causal relationship between vibration feature quantities and failure causes, that is, a failure cause-and-effect table. An example of such a database structure is shown in the table below.

【table】

Claims (1)

[Claims] 1 Input the vibration signal and rotation pulse signal obtained from the rotating machine that is the target of failure diagnosis, synchronize with the rotation pulse signal, make the interval between the rotation pulse signals a sampling pulse whose rotation frequency is multiplied, and set the sampling pulse as a timing. A signal input unit that A/D converts and outputs a vibration signal as a signal, and a failure cause-and-effect table that predetermines the cause-and-effect relationship between the vibration feature amount representing a failure of the rotating machine and the failure cause-and-effect relationship, and the failure cause-and-effect table is Failure cause-and-effect table memory consisting of a group of variables for converting into a deterioration index of 0 to 1 indicating the degree of deterioration for each cause of failure, and a group of weighting coefficients indicating the degree of causality between the deterioration index and each cause of failure. and a vibration signal input unit, which processes the vibration signal input from the signal input unit to calculate a plurality of vibration feature quantities, and calculates a plurality of vibration feature quantities from the vibration feature quantities stored in the failure cause-and-effect table storage unit and the failure cause-and-effect relationship. 1. A failure diagnosis device for a rotating machine, comprising: a failure cause estimating section that estimates various failure causes based on a database; and a result display section that displays estimation results from the failure cause estimating section.